LinkedIn has updated the algorithm for its ‘People you may know’ list. It ensures users that its recommendations will not rely on where they grew up, the school they went to, or where they currently work to build their professional networks.
LinkedIn’s ‘People you may know’ recommendations is key to guide user connections. So, the platform has improved its systems to avoid some user types from dominating the list.
“PYMK primarily uses data like the Economic Graph and platform interactions to mine features and use ML algorithms to come up with relevant recommendations. However, like any AI system, a significant challenge for the accuracy of this system is controlling for external sociological factors, like a member’s general visibility off-platform or the tendency for technologies (such as professional social networks or the internet) to be adopted gradually. This can lead to situations where AI-powered products can reflect an existing bias towards some groups of people over others,” explains LinkedIn.
For instance, high-profile users frequently show up in these recommendations because LinkedIn’s system uses interactions as a proxy for others to connect with.
“There are a subset of members on LinkedIn who receive a large number of connection requests, e.g., an influencer in an industry, a high-profile senior executive, or a recruiter from a big company. At a high level, having a disproportionate number of connection requests may appear to simply run counter to our stated goal of closing the network gap. However, it can also lead to the member’s network becoming overrun with feed updates and notifications that may seem random or from members who are only tangentially relevant to their own career,” adds LinkedIn.
These people may present as key connectors to opportunity. LinkedIn must highlight a wider range of recommendations to these users for optimal networking potential.
LinkedIn’s refined system seeks a better balance in recommendations. It showcases people with less connection requests to improve exposure. Thus, a wider pool will receive more requests.
This may not be a big shift on how you use LinkedIn. Initial results show the update reduced the connection requests for people overloaded with them. And it led to a small boost in requests for less popular users.
The project is LinkedIn’s ramped up effort to promote equal opportunity. It has given users more ways to find and discover professional connections. And it removed any potential bias due to their background.